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Modulation of Habitat-Based Conservation Plans by Fishery Opportunity Costs: A New Caledonia Case Study Using Fine-Scale Catch Data
Authors:Marilyn Deas  Serge Andréfou?t  Marc Léopold  Nicolas Guillemot
Institution:1. UR-CoRéUs, Institut de Recherche pour le Développement, Laboratoire d''Excellence, CORAIL, Nouméa, New Caledonia.; 2. UR-CoRéUs, Institut de Recherche pour le Développement, Laboratoire d''Excellence, CORAIL, Port-Vila, Vanuatu.; 3. Fisheries Department of Vanuatu, Port-Vila, Vanuatu.; 4. Nicolas Guillemot Consultant, Noumea, New Caledonia.; University of Waikato (National Institute of Water and Atmospheric Research), New Zealand,
Abstract:Numerous threats impact coral reefs and conservation actions are urgently needed. Fast production of marine habitat maps promotes the use of habitat-only conservation plans, where a given percentage of the area of each habitat is set as conservation objectives. However, marine reserves can impact access to fishing grounds and generate opportunity costs for fishers that need to be minimized. In New Caledonia (Southwest Pacific), we used fine-scale fishery catch maps to define nineteen opportunity costs layers (expressed as biomass catch loss) considering i) total catches, ii) target fish families, iii) local marine tenure, and iv) gear type. The expected lower impacts on fishery catch when using the different cost constraints were ranked according to effectiveness in decreasing the costs generated by the habitat-only scenarios. The exercise was done for two habitat maps with different thematic richness. In most cases, habitat conservation objectives remained achievable, but effectiveness varied widely between scenarios and between habitat maps. The results provide practical guidelines for coral reef conservation and management. Habitat-only scenarios can be used to initiate conservation projects with stakeholders but the costs induced by such scenarios can be lowered by up to 50–60% when detailed exhaustive fishery data are used. When using partial data, the gain would be only in the 15–25% range. The best compromises are achieved when using local data.
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